Google hat zum ersten Mal einen seiner eigenen KI-Chips in die Umlaufbahn gebracht. Ein Prototyp-Rechensatellit mit einer Google Tensor Processing Unit (TPU) an Bord startete mit einer SpaceX-Rakete von Kalifornien aus. Es ist der erste Hardwaretest von Project Suncatcher, dem Plan des Konzerns, große Rechencluster im Weltraum aufzubauen.
Am selben Tag veröffentlichte Google eine begutachtete Fassung seines Whitepapers zu Rechenzentren im Orbit. Das Papier legt dar, wie viel sich noch ändern muss, bevor die Idee praxistauglich wird, und vieles davon hängt davon ab, dass SpaceX' Starship weit häufiger fliegt als heute.
Was der Prototyp beweisen muss
Der Satellit wurde von Planet Labs auf einer seiner Standardplattformen gebaut. Seine Aufgabe ist eng umrissen: zeigen, dass eine TPU, Googles hauseigene Alternative zu Nvidias GPUs, im Orbit tatsächlich funktioniert.
Google has put one of its own AI chips into orbit for the first time. A prototype compute satellite carrying a Google Tensor Processing Unit (TPU) lifted off on a SpaceX rocket from California. It is the first hardware test of Project Suncatcher, the company's plan to build large compute clusters in space.
On the same day, Google published a peer-reviewed version of its white paper on orbital data centers. The paper sets out how much has to change before the idea becomes practical, and much of that depends on SpaceX's Starship flying far more often than it does today.
Shopify has launched Canvas, a site-building tool that lets merchants put together their online store through a conversation with AI. The company announced it on Thursday. The idea is straightforward: describe what you want, watch the store change, and keep refining until it looks right.
The change is less about adding AI to Shopify and more about how store building itself works on the platform.
From blocks and themes to a chat window
Shopify was not short on site-building options before Canvas. Its existing no-code builder was reasonably capable. Merchants picked a theme and then edited it by moving modular sections and blocks around. That approach covered a lot of ground, but it had a ceiling. Anything beyond the standard layout options meant opening the code or paying a developer.
Microsoft has added three new models to its MAI family, all aimed at the same goal: voice agents that can hold a conversation without awkward pauses. The headline release is MAI-Transcribe-2-Streaming, the company's first streaming transcription model. It ships alongside two text-to-speech models, MAI-Voice-2.1 and MAI-Voice-2.1-Flash.
The target audience is developers. Microsoft wants them to build agents that listen to a speaker and respond almost immediately, closer to the rhythm of a human conversation than the stop-and-wait pattern of many current assistants.
How the streaming model works
MAI-Transcribe-2-Streaming receives speech over a WebSocket connection and returns a transcript that keeps updating while the person is still talking. When the speaker stops, the model marks the transcript as final.
OpenAI is making another attempt at turning ChatGPT into a shopping companion. On Thursday, the company announced two new features rolling out globally: virtual try-on for clothing and accessories, and a Favorites function for saving products to look at later.
Neither idea is new to online retail. What matters here is the context. AI assistants are still trying to figure out where they fit in consumer shopping, and OpenAI's own track record in this area is mixed.
How virtual try-on works
The try-on feature asks users to upload a selfie or a full-body photo. ChatGPT then generates an image showing how a piece of clothing or an accessory might look on them. In shopping results, the option appears as a new Try On button.
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